<i>C14orf132</i> gene is possibly related to extremely low birth weight

BackgroundDespite extensive research the genetic component of extremely low birth weight (ELBW) in newborns has remained obscure.ResultsThe aim of the case study was to identify candidate gene(s) causing ELBW in newborns and hypotrophy in infants. A family of four was studied: mother, father and two ELBW-phenotype children. Studies were made of the medical conditions of the second child at birth and post-partum - peculiar phenotype, micro-anomalies, recurrent infections, suspicion of autoimmune hepatitis, multifactorial encephalopathy and suspected metabolic and chromosomal abnormalities. Whole genome single nucleotide polymorphism (SNP) genotyping array was used to investigate the genomic rearrangements in both affected children using peripheral blood DNA samples. Whole blood transcriptome was assessed by using RNA sequencing (RNA-seq) in all four family members. RNA-seq identified a single gene - C14orf132 (chromosome 14 open reading frame 132) differentially expressed, with the level of the transcript significantly lower in the blood samples of the children. Copy number variant (CNV) analysis did not reveal any pathogenic CNVs in the region of C14orf132 gene of both affected children.ConclusionWe demonstrated the importance of combining whole genome CNV and transcriptome analysis in identification of the candidate gene(s) in case studies. We propose the C14orf132 gene expression to be associated with the ELBW-phenotype. C14orf132 gene is a novel long non-coding RNA (lincRNA) with unknown function, which might be associated with the pre- and early postnatal developmental delay through the altered gene expression

Omics-informed CNV calls reduce false-positive rates and improve power for CNV-trait associations

Copy-number variations (CNV) are believed to play an important role in a wide range of complex traits, but discovering such associations remains challenging. While whole-genome sequencing (WGS) is the gold-standard approach for CNV detection, there are several orders of magnitude more samples with available genotyping microarray data. Such array data can be exploited for CNV detection using dedicated software (e.g., PennCNV); however, these calls suffer from elevated false-positive and -negative rates. In this study, we developed a CNV quality score that weights PennCNV calls (pCNVs) based on their likelihood of being true positive. First, we established a measure of pCNV reliability by leveraging evidence from multiple omics data (WGS, transcriptomics, and methylomics) obtained from the same samples. Next, we built a predictor of omics-confirmed pCNVs, termed omics-informed quality score (OQS), using only PennCNV software output parameters. Promisingly, OQS assigned to pCNVs detected in close family members was up to 35% higher than the OQS of pCNVs not carried by other relatives (p < 3.0 x 10(-90)), outperforming other scores. Finally, in an association study of four anthropometric traits in 89,516 Estonian Biobank samples, the use of OQS led to a relative increase in the trait variance explained by CNVs of up to 56% compared with published quality filtering methods or scores. Overall, we put forward a flexible framework to improve any CNV detection method leveraging multi-omics evidence, applied it to improve PennCNV calls, and demonstrated its utility by improving the statistical power for downstream association analyses.Peer reviewe

Diverse phenotype in patients with complex I deficiency due to mutations in NDUFB11

Contains fulltext : 209428.pdf (publisher's version ) (Closed access

In vitro fertilization does not increase the incidence of de novo copy number alterations in fetal and placental lineages

Although chromosomal instability (CIN) is a common phenomenon in cleavage-stage embryogenesis following in vitro fertilization (IVF)1-3, its rate in naturally conceived human embryos is unknown. CIN leads to mosaic embryos that contain a combination of genetically normal and abnormal cells, and is significantly higher in in vitro-produced preimplantation embryos as compared to in vivo-conceived preimplantation embryos4. Even though embryos with CIN-derived complex aneuploidies may arrest between the cleavage and blastocyst stages of embryogenesis5,6, a high number of embryos containing abnormal cells can pass this strong selection barrier7,8. However, neither the prevalence nor extent of CIN during prenatal development and at birth, following IVF treatment, is well understood. Here we profiled the genomic landscape of fetal and placental tissues postpartum from both IVF and naturally conceived children, to investigate the prevalence and persistence of large genetic aberrations that probably arose from IVF-related CIN. We demonstrate that CIN is not preserved at later stages of prenatal development, and that de novo numerical aberrations or large structural DNA imbalances occur at similar rates in IVF and naturally conceived live-born neonates. Our findings affirm that human IVF treatment has no detrimental effect on the chromosomal constitution of fetal and placental lineages.status: publishe

A cross-disorder dosage sensitivity map of the human genome

Rare copy-number variants (rCNVs) include deletions and duplications that occur infrequently in the global human population and can confer substantial risk for disease. In this study, we aimed to quantify the prop-erties of haploinsufficiency (i.e., deletion intolerance) and triplosensitivity (i.e., duplication intolerance) throughout the human genome. We harmonized and meta-analyzed rCNVs from nearly one million individuals to construct a genome-wide catalog of dosage sensitivity across 54 disorders, which defined 163 dosage sensitive segments associated with at least one disorder. These segments were typically gene dense and often harbored dominant dosage sensitive driver genes, which we were able to prioritize using statistical fine-mapping. Finally, we designed an ensemble machine-learning model to predict probabilities of dosage sensitivity (pHaplo & pTriplo) for all autosomal genes, which identified 2,987 haploinsufficient and 1,559 trip-losensitive genes, including 648 that were uniquely triplosensitive. This dosage sensitivity resource will pro-vide broad utility for human disease research and clinical genetics